Gigabyte SV S260-NF1 2U NVMe Over Fabric Storage 24x2.5 HS Retail
Gigabyte SV S260-NF1 2U NVMe Over Fabric Storage 24x2.5 HS Retail is backordered and will ship as soon as it is back in stock.
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Tariffs And Fees
Being a Canadian company, our U.S. shipments are subject to tariffs. Under DDP (Delivered Duty Paid), all applicable tariffs and fees are calculated and paid upfront at checkout.
Industrial Automation Parts is only an authorized distributor for DeLock and is not authorized for any other manufacturers. Manufacturer's warranty and support do not apply. Our IAP warranty of three months is applicable.
Country Of Origin: China
• Western Digital Onyx NVMe Over Fabric storage controller
• Fully supports iWARP, RoCE v1 and v2
• Dual controller architecture
• 1 x 100Gb/s or 2 x 50Gb/s Ethernet port(s) via QSFP28 interface
• 1 x AST2520 management port per node
• 24 x 2.5" NVMe hot-swappable bays
• 3 x PCIe Gen3 x16 slots per node
• Dual 800W 80 PLUS Platinum redundant power supply
NVMe Over Fabrics (NVMeOF)
Direct Attached NVMe Storage is Fast & Efficient, but Still Has Limitations…
• Direct attached NVMe storage has limited scalability, as PCIe is inherently not designed for expansion far outside the box.
• Direct attached storage offers little or no support for sharing of flash resources amongst multiple servers. Servers can only access flash in their own chassis.
• No sharing leads to storage utilization inefficiency and resource waste. Underutilized “stranded” or “dark” flash can be an issue
Bringing Scale-Out NVMe Storage Capabilities Independent of Compute
NVMe-OF enables NVMe-based communication over interconnects (“fabrics”) other than PCIe. This interface makes it possible to connect “external” storage enclosures to a server, either directly or through a switch, while still using NVMe as the fundamental communication mechanism. Flash storage can then be scaled out independent of compute.
Enabling Resource Disaggregation + Pooling to Maximize Efficiency & Minimize Under-utilization
Combined with virtualization, the amount and type of each resource (CPU, GPU, storage, networking) can be selected for each workload independent of where that resource is physically located in the data center.
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